We consider the Harvest domain from [1]}, in which agents move along a square grid to consume apples (by moving to them), and are given a reward of 1 for consuming these. However, apples regrow proportionally to the number of nearby apples, and thus, the dilemma here comes from managing the amount of consumption done by the agents to allow for regrowth. Here, for simplicity, instead of working with convolutional features, we provide all agents with engineered features (specifically, the agent's position and orientation, the coordinates and orientation of the closest agent, the position of the nearest apple, the number of close apples to the agent, the number of total apples, and the number of apples eaten by each agent in the last timestep). Moreover, we add the feature of all agent's density information to the individual agent's features for the case of gifting, to allow for gifting to be sufficiently expressive to emulate contracts. Also, to make the social dilemma more difficult, we remove the agent's ability to use the punishing beam to sanction other agent's behaviour (hence, making our results not directly comparable to [2]}).
